Organizations, irrespective of the kind of business they are involved in, are increasingly dependent on their computing facilities. Data-centers equipped with various computing systems, such as application servers, networking devices and storage devices, are deployed by the organizations to cater to the information or computing services requested by the users. Generally, computing devices, their cooling fans, and other peripheral devices are supplied with power for their proper functioning.
Given today's challenging business environment and environmental standards, such as, energy star rating system, many organizations are prompted to consider optimizing the power consumed by the various computing systems, in addition to paying attention to the traditional aspects of the data centers, such as the amount of data storage and the processing speed of the computing systems. In order to manage and optimize energy consumption, various techniques, such as consolidation or virtualization, are employed. The consolidation techniques optimize the energy consumption by reducing the number of the computing systems in a data center, while the virtualization techniques optimize the energy consumption by enhancing efficiency of the computing system without added hardware. These techniques are employed based on, among other things, energy consumed by the computing systems within the data centers. However, the conventional techniques may provide an incomplete profile of the energy consumption of the computing systems and the data centers. Consequently, the techniques employed to manage energy consumption may not be used to maximum potential.